TITLE:
#ISIS—A Comparative Analysis of Country-Specific Sentiment on Twitter
AUTHORS:
Sara Denise Ruhrberg, Giulia Kirstein, Tim Habermann, Janina Nikolic, Wolfgang G. Stock
KEYWORDS:
AFINN, ISIS, Terrorism, Sentiment Analysis, Data Analysis, Senti Strength, Emotions, Twitter, Hashtags, Emoticons
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.6 No.6,
June
19,
2018
ABSTRACT:
The aim of this study is to analyze tweets on Twitter to the topic Islamic State regarding their positive and negative emotions by performing a sentiment anal-ysis. People of different regions and cultures have a specific emotionality con-cerning the IS, not only in daily life but also in writing microblogs. With the help of sentiment analysis, the following question should be answered: “What are Twitter user’s opinions on ISIS in different states worldwide?” For this purpose, a Python tool is developed that interacts with the Twitter Streaming API to retrieve Tweets that are IS-related, saving them with associated countries. Close to 500,000 tweets are collected by this tool over a period of nearly six weeks. Sentiment analysis of Tweets is made with a tool invented by Janina Nikolic. Results are normalized with additional, self-developed Python scripts and analyzed with Microsoft Excel and IBM SPSS. The results show that most of the Tweets in the countries have a negative attitude towards the Islamic State, and only a very limited set of states has a neutral or positive total sentiment in the results of this study. Sentiment is influenced by various factors, including political systems, geographic location and distance towards the area where the Islamic State is active and terroristic attacks.